function ABCD_LRR_violin_acc_allsub(model_dir, metric, outdir, outstem, bhvr_ls, colloq_ls)

    % ABCD_KRR_whisker_acc_allsub(model_dir, metric, outdir, outname, bhvr_ls, colloq_ls)
    %
    % Plot the model performance in general (i.e. the accuracy on the whole test sets).
    
    addpath(genpath( fullfile(getenv('HOME'), 'storage', 'from_HOME', 'code', 'plotting_functions')))
    colormat = [200, 200, 200]./255;
    
    proj_dir = fullfile(getenv('HOME'), 'storage', 'MyProject', 'fairAI', 'ABCD_race');
    if(~exist('bhvr_ls', 'var') || isempty(bhvr_ls))
        bhvr_ls = fullfile(proj_dir, 'scripts', 'lists', 'behavior_list.txt');
    end
    if(~exist('colloq_ls', 'var') || isempty(colloq_ls))
        colloq_ls = fullfile(proj_dir, 'scripts', 'lists', 'colloquial_list.txt');
    end
    
    [bhvr_nm, nbhvr] = CBIG_text2cell(bhvr_ls);
    colloq_nm = CBIG_text2cell(colloq_ls);
    if(length(colloq_nm) ~= nbhvr)
        error('Length of behavioral names list and colloquial names list not equal.')
    end
    
    data = [];
    for b = 1:nbhvr
        final_result = load(fullfile(model_dir, bhvr_nm{b}, ...
            'results', 'optimal_acc', [bhvr_nm{b} '.mat']));
        Nfolds = length(final_result.optimal_statistics);
        curr_stats = zeros(Nfolds, 1);
        for f = 1:Nfolds
            curr_stats(f) = final_result.optimal_statistics{f}.(metric);
        end
        data = [data curr_stats];
    end
    [~, idx] = sort(mean(data,1), 'descend');
    data = data(:, idx);
    bhvr_nm = bhvr_nm(idx);
    colloq_nm = colloq_nm(idx);
    
    %% plot
    f = figure('visible', 'off');
    vio = violinplot(data, [], [], 'ViolinColor', colormat, 'ShowMean', true);
    for i = 1:length(vio)
        vio(i).ViolinPlot.LineWidth = 2;
        %vio(i).ScatterPlot.Marker = '.';
        vio(i).ScatterPlot.SizeData = 12;
        vio(i).MedianPlot.SizeData = 18;
    end
    hold on
    xlimit = get(gca, 'xlim');
    plot(xlimit, [0 0], ':k');
    hold off
    
    pf = get(gcf, 'position');
    set(gcf, 'position', [0 0 100+50*nbhvr 900])
    set(gca, 'position', [0.35 0.4 0.6 0.5])
    
    switch metric
        case 'corr'
            y_label = 'Cross-validated Pearson''s r';
        case 'predictive_COD'
            y_label = 'Cross-validated predictive COD';
        case 'COD'
            y_label = 'Cross-validated COD';
        otherwise
            error('Unknown metric')
    end
    yl = ylabel(y_label);
    set(yl, 'fontsize', 16, 'linewidth', 2)
    
    set(gca, 'xticklabel', colloq_nm, 'fontsize', 16, 'linewidth', 2);
    rotateXLabels( gca(), 45 );
    set(gca, 'tickdir', 'out', 'box', 'off')
    
    if(~exist(outdir, 'dir'))
        mkdir(outdir)
    end
    outname = fullfile(outdir, [outstem ]);
    export_fig(outname, '-png', '-nofontswap', '-a1');
    set(gcf, 'color', 'w');
    hgexport(f, outname)
    close
    
    rmpath(genpath( fullfile(getenv('HOME'), 'storage', 'from_HOME', 'code', 'plotting_functions')))
    
    end